Overview

Brought to you by YData

Dataset statistics

 Profiling Report - Train SetProfiling Report - Test Set
Number of variables1414
Number of observations535179
Missing cells00
Missing cells (%)0.0%0.0%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory62.7 KiB21.0 KiB
Average record size in memory120.0 B120.0 B

Variable types

 Profiling Report - Train SetProfiling Report - Test Set
Numeric1010
DateTime11
Categorical33

Alerts

Profiling Report - Train SetProfiling Report - Test Set
cdi is highly overall correlated with sigcdi is highly overall correlated with sigHigh correlation
dmin is highly overall correlated with nstdmin is highly overall correlated with nstHigh correlation
label is highly overall correlated with magType and 1 other fieldslabel is highly overall correlated with magType and 1 other fieldsHigh correlation
magType is highly overall correlated with label and 1 other fieldsmagType is highly overall correlated with labelHigh correlation
magnitude is highly overall correlated with sigmagnitude is highly overall correlated with sigHigh correlation
net is highly overall correlated with magTypeAlert not present in this datasetHigh correlation
nst is highly overall correlated with dmin and 1 other fieldsnst is highly overall correlated with dmin and 1 other fieldsHigh correlation
sig is highly overall correlated with cdi and 1 other fieldssig is highly overall correlated with cdi and 1 other fieldsHigh correlation
net is highly imbalanced (90.5%) net is highly imbalanced (89.8%) Imbalance
magType is highly imbalanced (52.0%) Alert not present in this datasetImbalance
cdi has 150 (28.0%) zeros cdi has 50 (27.9%) zeros Zeros
nst has 250 (46.7%) zeros nst has 83 (46.4%) zeros Zeros
dmin has 274 (51.2%) zeros dmin has 90 (50.3%) zeros Zeros
gap has 48 (9.0%) zeros gap has 13 (7.3%) zeros Zeros
Alert not present in this datasetlatitude has unique values Unique
Alert not present in this datasetlongitude has unique values Unique

Reproduction

 Profiling Report - Train SetProfiling Report - Test Set
Analysis started2024-11-12 04:13:51.2845122024-11-12 04:14:15.872878
Analysis finished2024-11-12 04:14:15.8599882024-11-12 04:14:39.325198
Duration24.58 seconds23.45 seconds
Software versionydata-profiling vv4.12.0ydata-profiling vv4.12.0
Download configurationconfig.jsonconfig.json

Variables

magnitude
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct1212
Distinct (%)2.2%6.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean6.83570096.8586592
 Profiling Report - Train SetProfiling Report - Test Set
Minimum6.56.5
Maximum7.67.6
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:40.071178image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum6.56.5
5-th percentile6.56.5
Q16.66.6
median6.86.8
Q377.1
95-th percentile7.57.5
Maximum7.67.6
Range1.11.1
Interquartile range (IQR)0.40.5

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation0.305958650.3051439
Coefficient of variation (CV)0.0447589290.044490313
Kurtosis-0.0568372-0.4929851
Mean6.83570096.8586592
Median Absolute Deviation (MAD)0.20.2
Skewness0.90389710.69270614
Sum3657.11227.7
Variance0.0936106970.093112799
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:40.521405image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
6.5 104
19.4%
6.7 81
15.1%
6.6 78
14.6%
6.8 62
11.6%
6.9 56
10.5%
7 35
 
6.5%
7.1 29
 
5.4%
7.2 22
 
4.1%
7.3 21
 
3.9%
7.6 18
 
3.4%
Other values (2) 29
 
5.4%
ValueCountFrequency (%)
6.6 37
20.7%
6.5 27
15.1%
6.9 21
11.7%
6.7 17
9.5%
6.8 16
8.9%
7.1 14
 
7.8%
7 14
 
7.8%
7.3 10
 
5.6%
7.2 8
 
4.5%
7.5 6
 
3.4%
Other values (2) 9
 
5.0%
ValueCountFrequency (%)
6.5 104
19.4%
6.6 78
14.6%
6.7 81
15.1%
6.8 62
11.6%
6.9 56
10.5%
7 35
 
6.5%
7.1 29
 
5.4%
7.2 22
 
4.1%
7.3 21
 
3.9%
7.4 13
 
2.4%
ValueCountFrequency (%)
6.5 27
15.1%
6.6 37
20.7%
6.7 17
9.5%
6.8 16
8.9%
6.9 21
11.7%
7 14
 
7.8%
7.1 14
 
7.8%
7.2 8
 
4.5%
7.3 10
 
5.6%
7.4 5
 
2.8%
ValueCountFrequency (%)
6.5 27
5.0%
6.6 37
6.9%
6.7 17
3.2%
6.8 16
3.0%
6.9 21
3.9%
7 14
 
2.6%
7.1 14
 
2.6%
7.2 8
 
1.5%
7.3 10
 
1.9%
7.4 5
 
0.9%
ValueCountFrequency (%)
6.5 104
58.1%
6.6 78
43.6%
6.7 81
45.3%
6.8 62
34.6%
6.9 56
31.3%
7 35
 
19.6%
7.1 29
 
16.2%
7.2 22
 
12.3%
7.3 21
 
11.7%
7.4 13
 
7.3%
 Profiling Report - Train SetProfiling Report - Test Set
Distinct532178
Distinct (%)99.4%99.4%
Missing00
Missing (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
 Profiling Report - Train SetProfiling Report - Test Set
Minimum2001-01-01 08:54:002001-01-01 06:57:00
Maximum2022-11-18 13:37:002022-12-11 07:09:00
2024-11-11T23:14:40.981754image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-11T23:14:41.502121image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

cdi
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct1010
Distinct (%)1.9%5.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.11028044.3407821
 Profiling Report - Train SetProfiling Report - Test Set
Minimum00
Maximum99
Zeros15050
Zeros (%)28.0%27.9%
Negative00
Negative (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:41.883039image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum00
5-th percentile00
Q100
median55
Q377
95-th percentile99
Maximum99
Range99
Interquartile range (IQR)77

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation3.09478643.1553524
Coefficient of variation (CV)0.752938040.72690873
Kurtosis-1.3656772-1.342476
Mean4.11028044.3407821
Median Absolute Deviation (MAD)22
Skewness-0.13214471-0.23870241
Sum2199777
Variance9.57770319.9562488
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:42.129317image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 150
28.0%
5 79
14.8%
7 66
12.3%
8 53
 
9.9%
6 52
 
9.7%
4 46
 
8.6%
3 32
 
6.0%
9 32
 
6.0%
2 13
 
2.4%
1 12
 
2.2%
ValueCountFrequency (%)
0 50
27.9%
7 24
13.4%
5 23
12.8%
6 22
12.3%
8 18
 
10.1%
3 15
 
8.4%
9 14
 
7.8%
4 11
 
6.1%
1 1
 
0.6%
2 1
 
0.6%
ValueCountFrequency (%)
0 150
28.0%
1 12
 
2.2%
2 13
 
2.4%
3 32
 
6.0%
4 46
 
8.6%
5 79
14.8%
6 52
 
9.7%
7 66
12.3%
8 53
 
9.9%
9 32
 
6.0%
ValueCountFrequency (%)
0 50
27.9%
1 1
 
0.6%
2 1
 
0.6%
3 15
 
8.4%
4 11
 
6.1%
5 23
12.8%
6 22
12.3%
7 24
13.4%
8 18
 
10.1%
9 14
 
7.8%
ValueCountFrequency (%)
0 50
9.3%
1 1
 
0.2%
2 1
 
0.2%
3 15
 
2.8%
4 11
 
2.1%
5 23
4.3%
6 22
4.1%
7 24
4.5%
8 18
 
3.4%
9 14
 
2.6%
ValueCountFrequency (%)
0 150
83.8%
1 12
 
6.7%
2 13
 
7.3%
3 32
 
17.9%
4 46
 
25.7%
5 79
44.1%
6 52
 
29.1%
7 66
36.9%
8 53
 
29.6%
9 32
 
17.9%

mmi
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct98
Distinct (%)1.7%4.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.82056076.0111732
 Profiling Report - Train SetProfiling Report - Test Set
Minimum12
Maximum99
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:42.349348image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum12
5-th percentile34
Q155
median66
Q377
95-th percentile88
Maximum99
Range87
Interquartile range (IQR)22

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation1.42396151.3820227
Coefficient of variation (CV)0.244643350.22990899
Kurtosis-0.14095848-0.11126406
Mean5.82056076.0111732
Median Absolute Deviation (MAD)11
Skewness-0.27084318-0.29142078
Sum31141076
Variance2.02766641.9099868
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:42.631299image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
6 147
27.5%
7 138
25.8%
5 105
19.6%
4 63
11.8%
8 34
 
6.4%
3 31
 
5.8%
9 13
 
2.4%
2 3
 
0.6%
1 1
 
0.2%
ValueCountFrequency (%)
7 51
28.5%
6 49
27.4%
5 33
18.4%
4 18
 
10.1%
8 15
 
8.4%
3 7
 
3.9%
9 5
 
2.8%
2 1
 
0.6%
ValueCountFrequency (%)
1 1
 
0.2%
2 3
 
0.6%
3 31
 
5.8%
4 63
11.8%
5 105
19.6%
6 147
27.5%
7 138
25.8%
8 34
 
6.4%
9 13
 
2.4%
ValueCountFrequency (%)
2 1
 
0.6%
3 7
 
3.9%
4 18
 
10.1%
5 33
18.4%
6 49
27.4%
7 51
28.5%
8 15
 
8.4%
9 5
 
2.8%
ValueCountFrequency (%)
2 1
 
0.2%
3 7
 
1.3%
4 18
 
3.4%
5 33
6.2%
6 49
9.2%
7 51
9.5%
8 15
 
2.8%
9 5
 
0.9%
ValueCountFrequency (%)
1 1
 
0.6%
2 3
 
1.7%
3 31
 
17.3%
4 63
35.2%
5 105
58.7%
6 147
82.1%
7 138
77.1%
8 34
 
19.0%
9 13
 
7.3%

sig
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct236115
Distinct (%)44.1%64.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean822.38318867.87709
 Profiling Report - Train SetProfiling Report - Test Set
Minimum650650
Maximum27902910
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:43.024612image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum650650
5-th percentile650650
Q1691682
median733759
Q3836.5872.5
95-th percentile1429.81544.1
Maximum27902910
Range21402260
Interquartile range (IQR)145.5190.5

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation256.80398347.26648
Coefficient of variation (CV)0.312268040.40013325
Kurtosis14.24886914.758287
Mean822.38318867.87709
Median Absolute Deviation (MAD)6389
Skewness3.26892013.5183737
Sum439975155350
Variance65948.285120594.01
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:43.505205image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
650 38
 
7.1%
691 33
 
6.2%
670 23
 
4.3%
711 21
 
3.9%
732 13
 
2.4%
776 13
 
2.4%
820 9
 
1.7%
651 8
 
1.5%
733 7
 
1.3%
798 7
 
1.3%
Other values (226) 363
67.9%
ValueCountFrequency (%)
670 18
 
10.1%
650 12
 
6.7%
776 5
 
2.8%
711 4
 
2.2%
744 3
 
1.7%
651 3
 
1.7%
740 3
 
1.7%
674 3
 
1.7%
842 3
 
1.7%
820 3
 
1.7%
Other values (105) 122
68.2%
ValueCountFrequency (%)
650 38
7.1%
651 8
 
1.5%
652 5
 
0.9%
653 3
 
0.6%
654 3
 
0.6%
655 3
 
0.6%
656 1
 
0.2%
657 4
 
0.7%
659 1
 
0.2%
661 1
 
0.2%
ValueCountFrequency (%)
650 12
6.7%
651 3
 
1.7%
652 1
 
0.6%
653 2
 
1.1%
656 1
 
0.6%
670 18
10.1%
671 1
 
0.6%
674 3
 
1.7%
677 2
 
1.1%
678 1
 
0.6%
ValueCountFrequency (%)
650 12
2.2%
651 3
 
0.6%
652 1
 
0.2%
653 2
 
0.4%
656 1
 
0.2%
670 18
3.4%
671 1
 
0.2%
674 3
 
0.6%
677 2
 
0.4%
678 1
 
0.2%
ValueCountFrequency (%)
650 38
21.2%
651 8
 
4.5%
652 5
 
2.8%
653 3
 
1.7%
654 3
 
1.7%
655 3
 
1.7%
656 1
 
0.6%
657 4
 
2.2%
659 1
 
0.6%
661 1
 
0.6%

net
Categorical

 Profiling Report - Train SetProfiling Report - Test Set
Distinct95
Distinct (%)1.7%2.8%
Missing00
Missing (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
us
517 
ak
 
7
pt
 
2
nc
 
2
hv
 
2
Other values (4)
 
5
us
174 
ak
 
2
nc
 
1
duputel
 
1
ci
 
1

Length

 Profiling Report - Train SetProfiling Report - Test Set
Max length27
Median length22
Mean length22.027933
Min length22

Characters and Unicode

 Profiling Report - Train SetProfiling Report - Test Set
Total characters1070363
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report - Train SetProfiling Report - Test Set
Unique33 ?
Unique (%)0.6%1.7%

Sample

 Profiling Report - Train SetProfiling Report - Test Set
1st rowusus
2nd rowusus
3rd rowusus
4th rowusus
5th rowusus

Common Values

ValueCountFrequency (%)
us 517
96.6%
ak 7
 
1.3%
pt 2
 
0.4%
nc 2
 
0.4%
hv 2
 
0.4%
at 2
 
0.4%
nn 1
 
0.2%
ci 1
 
0.2%
uw 1
 
0.2%
ValueCountFrequency (%)
us 174
97.2%
ak 2
 
1.1%
nc 1
 
0.6%
duputel 1
 
0.6%
ci 1
 
0.6%

Length

2024-11-11T23:14:43.801511image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report - Train Set

2024-11-11T23:14:44.088615image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:44.431550image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
us 517
96.6%
ak 7
 
1.3%
pt 2
 
0.4%
nc 2
 
0.4%
hv 2
 
0.4%
at 2
 
0.4%
nn 1
 
0.2%
ci 1
 
0.2%
uw 1
 
0.2%
ValueCountFrequency (%)
us 174
97.2%
ak 2
 
1.1%
nc 1
 
0.6%
duputel 1
 
0.6%
ci 1
 
0.6%

Most occurring characters

ValueCountFrequency (%)
u 518
48.4%
s 517
48.3%
a 9
 
0.8%
k 7
 
0.7%
t 4
 
0.4%
n 4
 
0.4%
c 3
 
0.3%
p 2
 
0.2%
h 2
 
0.2%
v 2
 
0.2%
Other values (2) 2
 
0.2%
ValueCountFrequency (%)
u 176
48.5%
s 174
47.9%
a 2
 
0.6%
k 2
 
0.6%
c 2
 
0.6%
n 1
 
0.3%
d 1
 
0.3%
p 1
 
0.3%
t 1
 
0.3%
e 1
 
0.3%
Other values (2) 2
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1070
100.0%
ValueCountFrequency (%)
(unknown) 363
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
u 518
48.4%
s 517
48.3%
a 9
 
0.8%
k 7
 
0.7%
t 4
 
0.4%
n 4
 
0.4%
c 3
 
0.3%
p 2
 
0.2%
h 2
 
0.2%
v 2
 
0.2%
Other values (2) 2
 
0.2%
ValueCountFrequency (%)
u 176
48.5%
s 174
47.9%
a 2
 
0.6%
k 2
 
0.6%
c 2
 
0.6%
n 1
 
0.3%
d 1
 
0.3%
p 1
 
0.3%
t 1
 
0.3%
e 1
 
0.3%
Other values (2) 2
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1070
100.0%
ValueCountFrequency (%)
(unknown) 363
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
u 518
48.4%
s 517
48.3%
a 9
 
0.8%
k 7
 
0.7%
t 4
 
0.4%
n 4
 
0.4%
c 3
 
0.3%
p 2
 
0.2%
h 2
 
0.2%
v 2
 
0.2%
Other values (2) 2
 
0.2%
ValueCountFrequency (%)
u 176
48.5%
s 174
47.9%
a 2
 
0.6%
k 2
 
0.6%
c 2
 
0.6%
n 1
 
0.3%
d 1
 
0.3%
p 1
 
0.3%
t 1
 
0.3%
e 1
 
0.3%
Other values (2) 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1070
100.0%
ValueCountFrequency (%)
(unknown) 363
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
u 518
48.4%
s 517
48.3%
a 9
 
0.8%
k 7
 
0.7%
t 4
 
0.4%
n 4
 
0.4%
c 3
 
0.3%
p 2
 
0.2%
h 2
 
0.2%
v 2
 
0.2%
Other values (2) 2
 
0.2%
ValueCountFrequency (%)
u 176
48.5%
s 174
47.9%
a 2
 
0.6%
k 2
 
0.6%
c 2
 
0.6%
n 1
 
0.3%
d 1
 
0.3%
p 1
 
0.3%
t 1
 
0.3%
e 1
 
0.3%
Other values (2) 2
 
0.6%

nst
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct23387
Distinct (%)43.6%48.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean227.16075229.82123
 Profiling Report - Train SetProfiling Report - Test Set
Minimum00
Maximum934782
Zeros25083
Zeros (%)46.7%46.4%
Negative00
Negative (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:44.781925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum00
5-th percentile00
Q100
median131141
Q3444420.5
95-th percentile667.3645.4
Maximum934782
Range934782
Interquartile range (IQR)444420.5

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation248.96027247.56305
Coefficient of variation (CV)1.09596521.0771983
Kurtosis-1.0246234-1.2685956
Mean227.16075229.82123
Median Absolute Deviation (MAD)131141
Skewness0.565024750.47986893
Sum12153141138
Variance61981.21461287.462
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:45.142618image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 250
46.7%
445 3
 
0.6%
444 3
 
0.6%
447 3
 
0.6%
426 3
 
0.6%
529 3
 
0.6%
698 3
 
0.6%
596 3
 
0.6%
243 2
 
0.4%
117 2
 
0.4%
Other values (223) 260
48.6%
ValueCountFrequency (%)
0 83
46.4%
640 3
 
1.7%
398 3
 
1.7%
420 2
 
1.1%
282 2
 
1.1%
494 2
 
1.1%
305 2
 
1.1%
312 2
 
1.1%
550 2
 
1.1%
561 1
 
0.6%
Other values (77) 77
43.0%
ValueCountFrequency (%)
0 250
46.7%
20 1
 
0.2%
23 1
 
0.2%
27 1
 
0.2%
43 1
 
0.2%
50 1
 
0.2%
63 1
 
0.2%
64 1
 
0.2%
65 1
 
0.2%
67 1
 
0.2%
ValueCountFrequency (%)
0 83
46.4%
10 1
 
0.6%
51 1
 
0.6%
111 1
 
0.6%
117 1
 
0.6%
131 1
 
0.6%
139 1
 
0.6%
141 1
 
0.6%
144 1
 
0.6%
147 1
 
0.6%
ValueCountFrequency (%)
0 83
15.5%
10 1
 
0.2%
51 1
 
0.2%
111 1
 
0.2%
117 1
 
0.2%
131 1
 
0.2%
139 1
 
0.2%
141 1
 
0.2%
144 1
 
0.2%
147 1
 
0.2%
ValueCountFrequency (%)
0 250
139.7%
20 1
 
0.6%
23 1
 
0.6%
27 1
 
0.6%
43 1
 
0.6%
50 1
 
0.6%
63 1
 
0.6%
64 1
 
0.6%
65 1
 
0.6%
67 1
 
0.6%

dmin
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct25690
Distinct (%)47.9%50.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean1.32039031.4262749
 Profiling Report - Train SetProfiling Report - Test Set
Minimum00
Maximum15.39417.654
Zeros27490
Zeros (%)51.2%50.3%
Negative00
Negative (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:45.611614image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum00
5-th percentile00
Q100
median00
Q32.0071.805
95-th percentile5.48156.4026
Maximum15.39417.654
Range15.39417.654
Interquartile range (IQR)2.0071.805

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation2.11798692.543312
Coefficient of variation (CV)1.60406121.783185
Kurtosis7.576571311.832219
Mean1.32039031.4262749
Median Absolute Deviation (MAD)00
Skewness2.38849132.9725409
Sum706.40882255.3032
Variance4.48586866.4684357
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:46.021408image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 274
51.2%
1.778 2
 
0.4%
0.828 2
 
0.4%
2.705 2
 
0.4%
1.505 2
 
0.4%
0.778 2
 
0.4%
1.487 2
 
0.4%
0.803 1
 
0.2%
6.012 1
 
0.2%
1.747 1
 
0.2%
Other values (246) 246
46.0%
ValueCountFrequency (%)
0 90
50.3%
0.289 1
 
0.6%
3.77 1
 
0.6%
11.764 1
 
0.6%
3.144 1
 
0.6%
1.504 1
 
0.6%
3.997 1
 
0.6%
1.872 1
 
0.6%
0.761 1
 
0.6%
0.356 1
 
0.6%
Other values (80) 80
44.7%
ValueCountFrequency (%)
0 274
51.2%
0.04616 1
 
0.2%
0.04685 1
 
0.2%
0.07 1
 
0.2%
0.11 1
 
0.2%
0.142 1
 
0.2%
0.151 1
 
0.2%
0.173 1
 
0.2%
0.225 1
 
0.2%
0.23 1
 
0.2%
ValueCountFrequency (%)
0 90
50.3%
0.135 1
 
0.6%
0.174 1
 
0.6%
0.281 1
 
0.6%
0.289 1
 
0.6%
0.312 1
 
0.6%
0.3225 1
 
0.6%
0.349 1
 
0.6%
0.355 1
 
0.6%
0.356 1
 
0.6%
ValueCountFrequency (%)
0 90
16.8%
0.135 1
 
0.2%
0.174 1
 
0.2%
0.281 1
 
0.2%
0.289 1
 
0.2%
0.312 1
 
0.2%
0.3225 1
 
0.2%
0.349 1
 
0.2%
0.355 1
 
0.2%
0.356 1
 
0.2%
ValueCountFrequency (%)
0 274
153.1%
0.04616 1
 
0.6%
0.04685 1
 
0.6%
0.07 1
 
0.6%
0.11 1
 
0.6%
0.142 1
 
0.6%
0.151 1
 
0.6%
0.173 1
 
0.6%
0.225 1
 
0.6%
0.23 1
 
0.6%

gap
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct20897
Distinct (%)38.9%54.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean25.05250526.787151
 Profiling Report - Train SetProfiling Report - Test Set
Minimum00
Maximum229239
Zeros4813
Zeros (%)9.0%7.3%
Negative00
Negative (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:46.632013image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum00
5-th percentile00
Q114.4516
median2021.5
Q33031.65
95-th percentile56.354.01
Maximum229239
Range229239
Interquartile range (IQR)15.5515.65

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation24.13376626.930727
Coefficient of variation (CV)0.963327461.0053599
Kurtosis28.66943635.9366
Mean25.05250526.787151
Median Absolute Deviation (MAD)77.5
Skewness4.41394295.1957495
Sum13403.094794.9
Variance582.43865725.26405
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:47.131729image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 48
 
9.0%
18 18
 
3.4%
16 17
 
3.2%
19 16
 
3.0%
12 14
 
2.6%
22 13
 
2.4%
15 12
 
2.2%
17 11
 
2.1%
14 11
 
2.1%
20 10
 
1.9%
Other values (198) 365
68.2%
ValueCountFrequency (%)
0 13
 
7.3%
17 6
 
3.4%
22 6
 
3.4%
11 6
 
3.4%
14 5
 
2.8%
23 5
 
2.8%
18 5
 
2.8%
16 5
 
2.8%
25 5
 
2.8%
17.7 4
 
2.2%
Other values (87) 119
66.5%
ValueCountFrequency (%)
0 48
9.0%
8 1
 
0.2%
8.7 1
 
0.2%
9 6
 
1.1%
9.5 1
 
0.2%
10 6
 
1.1%
10.1 2
 
0.4%
10.2 1
 
0.2%
10.6 1
 
0.2%
10.9 1
 
0.2%
ValueCountFrequency (%)
0 13
7.3%
10 1
 
0.6%
10.1 1
 
0.6%
11 6
3.4%
11.4 1
 
0.6%
11.5 1
 
0.6%
12 3
 
1.7%
12.1 1
 
0.6%
12.6 1
 
0.6%
13 2
 
1.1%
ValueCountFrequency (%)
0 13
2.4%
10 1
 
0.2%
10.1 1
 
0.2%
11 6
1.1%
11.4 1
 
0.2%
11.5 1
 
0.2%
12 3
 
0.6%
12.1 1
 
0.2%
12.6 1
 
0.2%
13 2
 
0.4%
ValueCountFrequency (%)
0 48
26.8%
8 1
 
0.6%
8.7 1
 
0.6%
9 6
 
3.4%
9.5 1
 
0.6%
10 6
 
3.4%
10.1 2
 
1.1%
10.2 1
 
0.6%
10.6 1
 
0.6%
10.9 1
 
0.6%

magType
Categorical

 Profiling Report - Train SetProfiling Report - Test Set
Distinct95
Distinct (%)1.7%2.8%
Missing00
Missing (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
mww
318 
mwc
150 
mwb
47 
mw
 
10
Mi
 
4
Other values (4)
 
6
mww
108 
mwc
45 
mwb
22 
mw
 
3
mb
 
1

Length

 Profiling Report - Train SetProfiling Report - Test Set
Max length33
Median length33
Mean length2.96261682.9776536
Min length22

Characters and Unicode

 Profiling Report - Train SetProfiling Report - Test Set
Total characters1585533
Distinct characters94
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report - Train SetProfiling Report - Test Set
Unique21 ?
Unique (%)0.4%0.6%

Sample

 Profiling Report - Train SetProfiling Report - Test Set
1st rowmwwmb
2nd rowmwcmwc
3rd rowmwwmww
4th rowmwbmwc
5th rowmwwmww

Common Values

ValueCountFrequency (%)
mww 318
59.4%
mwc 150
28.0%
mwb 47
 
8.8%
mw 10
 
1.9%
Mi 4
 
0.7%
ms 2
 
0.4%
md 2
 
0.4%
ml 1
 
0.2%
mb 1
 
0.2%
ValueCountFrequency (%)
mww 108
60.3%
mwc 45
25.1%
mwb 22
 
12.3%
mw 3
 
1.7%
mb 1
 
0.6%

Length

2024-11-11T23:14:47.470898image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report - Train Set

2024-11-11T23:14:47.783220image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:48.114103image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
mww 318
59.4%
mwc 150
28.0%
mwb 47
 
8.8%
mw 10
 
1.9%
mi 4
 
0.7%
ms 2
 
0.4%
md 2
 
0.4%
ml 1
 
0.2%
mb 1
 
0.2%
ValueCountFrequency (%)
mww 108
60.3%
mwc 45
25.1%
mwb 22
 
12.3%
mw 3
 
1.7%
mb 1
 
0.6%

Most occurring characters

ValueCountFrequency (%)
w 843
53.2%
m 531
33.5%
c 150
 
9.5%
b 48
 
3.0%
M 4
 
0.3%
i 4
 
0.3%
s 2
 
0.1%
d 2
 
0.1%
l 1
 
0.1%
ValueCountFrequency (%)
w 286
53.7%
m 179
33.6%
c 45
 
8.4%
b 23
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1585
100.0%
ValueCountFrequency (%)
(unknown) 533
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
w 843
53.2%
m 531
33.5%
c 150
 
9.5%
b 48
 
3.0%
M 4
 
0.3%
i 4
 
0.3%
s 2
 
0.1%
d 2
 
0.1%
l 1
 
0.1%
ValueCountFrequency (%)
w 286
53.7%
m 179
33.6%
c 45
 
8.4%
b 23
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1585
100.0%
ValueCountFrequency (%)
(unknown) 533
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
w 843
53.2%
m 531
33.5%
c 150
 
9.5%
b 48
 
3.0%
M 4
 
0.3%
i 4
 
0.3%
s 2
 
0.1%
d 2
 
0.1%
l 1
 
0.1%
ValueCountFrequency (%)
w 286
53.7%
m 179
33.6%
c 45
 
8.4%
b 23
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1585
100.0%
ValueCountFrequency (%)
(unknown) 533
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
w 843
53.2%
m 531
33.5%
c 150
 
9.5%
b 48
 
3.0%
M 4
 
0.3%
i 4
 
0.3%
s 2
 
0.1%
d 2
 
0.1%
l 1
 
0.1%
ValueCountFrequency (%)
w 286
53.7%
m 179
33.6%
c 45
 
8.4%
b 23
 
4.3%

depth
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct219103
Distinct (%)40.9%57.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean76.68309272.091832
 Profiling Report - Train SetProfiling Report - Test Set
Minimum2.76.43
Maximum660630
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:48.505835image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum2.76.43
5-th percentile9.9919.9987
Q11316.33
median26.5925.5
Q348.555.5
95-th percentile527.6314.3
Maximum660630
Range657.3623.57
Interquartile range (IQR)35.539.17

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation137.77921127.63336
Coefficient of variation (CV)1.79673511.7704275
Kurtosis7.700229910.983256
Mean76.68309272.091832
Median Absolute Deviation (MAD)14.5914.5
Skewness2.91389623.3485216
Sum41025.45412904.438
Variance18983.10916290.275
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:48.898302image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 68
 
12.7%
20 22
 
4.1%
35 19
 
3.6%
12 17
 
3.2%
33 14
 
2.6%
11 13
 
2.4%
28 10
 
1.9%
13 10
 
1.9%
24 10
 
1.9%
30 9
 
1.7%
Other values (209) 343
64.1%
ValueCountFrequency (%)
10 17
 
9.5%
33 8
 
4.5%
21 7
 
3.9%
24 6
 
3.4%
25 5
 
2.8%
22 5
 
2.8%
18 4
 
2.2%
17 4
 
2.2%
11 4
 
2.2%
19 4
 
2.2%
Other values (93) 115
64.2%
ValueCountFrequency (%)
2.7 1
 
0.2%
4.2 1
 
0.2%
5 3
0.6%
5.81 1
 
0.2%
6 1
 
0.2%
6.43 1
 
0.2%
7 1
 
0.2%
7.8 1
 
0.2%
8 5
0.9%
8.2 1
 
0.2%
ValueCountFrequency (%)
6.43 1
 
0.6%
6.8 1
 
0.6%
7 1
 
0.6%
8 2
 
1.1%
9 3
 
1.7%
9.987 1
 
0.6%
10 17
9.5%
11 4
 
2.2%
12 3
 
1.7%
13 2
 
1.1%
ValueCountFrequency (%)
6.43 1
 
0.2%
6.8 1
 
0.2%
7 1
 
0.2%
8 2
 
0.4%
9 3
 
0.6%
9.987 1
 
0.2%
10 17
3.2%
11 4
 
0.7%
12 3
 
0.6%
13 2
 
0.4%
ValueCountFrequency (%)
2.7 1
 
0.6%
4.2 1
 
0.6%
5 3
1.7%
5.81 1
 
0.6%
6 1
 
0.6%
6.43 1
 
0.6%
7 1
 
0.6%
7.8 1
 
0.6%
8 5
2.8%
8.2 1
 
0.6%

latitude
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct532179
Distinct (%)99.4%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean3.84070541.777138
 Profiling Report - Train SetProfiling Report - Test Set
Minimum-61.8484-60.857
Maximum71.631260.491
Zeros00
Zeros (%)0.0%0.0%
Negative29099
Negative (%)54.2%55.3%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:49.365916image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum-61.8484-60.857
5-th percentile-36.4949-37.39224
Q1-13.6345-15.28905
median-2.6286-3.517
Q324.404519.4375
95-th percentile51.959943.1375
Maximum71.631260.491
Range133.4796121.348
Interquartile range (IQR)38.03934.72655

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation26.99931526.481117
Coefficient of variation (CV)7.029780214.900991
Kurtosis-0.4163055-0.5193434
Mean3.84070541.777138
Median Absolute Deviation (MAD)16.729616.868
Skewness0.217188030.1693273
Sum2054.7774318.1077
Variance728.96302701.24958
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:49.808016image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.271 2
 
0.4%
52.48 2
 
0.4%
52.502 2
 
0.4%
-13.093 1
 
0.2%
28.412 1
 
0.2%
-3.6849 1
 
0.2%
7.929 1
 
0.2%
52.235 1
 
0.2%
67.631 1
 
0.2%
-20.671 1
 
0.2%
Other values (522) 522
97.6%
ValueCountFrequency (%)
36.166 1
 
0.6%
13.088 1
 
0.6%
14.6802 1
 
0.6%
-8.207 1
 
0.6%
-11.0355 1
 
0.6%
-28.4792 1
 
0.6%
-2.13 1
 
0.6%
3.8965 1
 
0.6%
-29.539 1
 
0.6%
-6.224 1
 
0.6%
Other values (169) 169
94.4%
ValueCountFrequency (%)
-61.8484 1
0.2%
-60.532 1
0.2%
-60.3026 1
0.2%
-60.2627 1
0.2%
-60.2152 1
0.2%
-60.1023 1
0.2%
-58.6262 1
0.2%
-58.5446 1
0.2%
-57.5959 1
0.2%
-56.2409 1
0.2%
ValueCountFrequency (%)
-60.857 1
0.6%
-58.3814 1
0.6%
-56.414 1
0.6%
-54.2189 1
0.6%
-44.796 1
0.6%
-43.4064 1
0.6%
-42.3205 1
0.6%
-38.355 1
0.6%
-37.695 1
0.6%
-37.3586 1
0.6%
ValueCountFrequency (%)
-60.857 1
0.2%
-58.3814 1
0.2%
-56.414 1
0.2%
-54.2189 1
0.2%
-44.796 1
0.2%
-43.4064 1
0.2%
-42.3205 1
0.2%
-38.355 1
0.2%
-37.695 1
0.2%
-37.3586 1
0.2%
ValueCountFrequency (%)
-61.8484 1
0.6%
-60.532 1
0.6%
-60.3026 1
0.6%
-60.2627 1
0.6%
-60.2152 1
0.6%
-60.1023 1
0.6%
-58.6262 1
0.6%
-58.5446 1
0.6%
-57.5959 1
0.6%
-56.2409 1
0.6%

longitude
Real number (ℝ)

 Profiling Report - Train SetProfiling Report - Test Set
Distinct532179
Distinct (%)99.4%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean57.09616244.459302
 Profiling Report - Train SetProfiling Report - Test Set
Minimum-179.968-178.6
Maximum179.662179.146
Zeros00
Zeros (%)0.0%0.0%
Negative17065
Negative (%)31.8%36.3%
Memory size8.4 KiB2.8 KiB
2024-11-11T23:14:50.246088image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Profiling Report - Train SetProfiling Report - Test Set
Minimum-179.968-178.6
5-th percentile-173.6156-176.3679
Q1-71.3876-72.1936
median122.12999.891
Q3151.2265142.967
95-th percentile169.2107167.5197
Maximum179.662179.146
Range359.63357.746
Interquartile range (IQR)222.6141215.1606

Descriptive statistics

 Profiling Report - Train SetProfiling Report - Test Set
Standard deviation117.33709117.01292
Coefficient of variation (CV)2.05507852.6319109
Kurtosis-0.98769818-1.2268982
Mean57.09616244.459302
Median Absolute Deviation (MAD)43.45965.25
Skewness-0.77571637-0.57361607
Sum30546.4477958.215
Variance13767.99413692.024
MonotonicityNot monotonicNot monotonic
2024-11-11T23:14:50.753695image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
168.892 2
 
0.4%
-167.736 2
 
0.4%
-168.08 2
 
0.4%
166.497 1
 
0.2%
59.18 1
 
0.2%
152.792 1
 
0.2%
-82.793 1
 
0.2%
151.444 1
 
0.2%
142.508 1
 
0.2%
169.716 1
 
0.2%
Other values (522) 522
97.6%
ValueCountFrequency (%)
141.562 1
 
0.6%
144.619 1
 
0.6%
-92.4527 1
 
0.6%
118.631 1
 
0.6%
-70.8284 1
 
0.6%
-176.619 1
 
0.6%
99.627 1
 
0.6%
126.862 1
 
0.6%
-176.34 1
 
0.6%
29.83 1
 
0.6%
Other values (169) 169
94.4%
ValueCountFrequency (%)
-179.968 1
0.2%
-179.511 1
0.2%
-179.373 1
0.2%
-178.959 1
0.2%
-178.927 1
0.2%
-178.804 1
0.2%
-178.57 1
0.2%
-178.244 1
0.2%
-178.204 1
0.2%
-178.1 1
0.2%
ValueCountFrequency (%)
-178.6 1
0.6%
-178.4 1
0.6%
-178.346 1
0.6%
-178.323 1
0.6%
-177.881 1
0.6%
-177.838 1
0.6%
-177.759 1
0.6%
-177.74 1
0.6%
-176.619 1
0.6%
-176.34 1
0.6%
ValueCountFrequency (%)
-178.6 1
0.2%
-178.4 1
0.2%
-178.346 1
0.2%
-178.323 1
0.2%
-177.881 1
0.2%
-177.838 1
0.2%
-177.759 1
0.2%
-177.74 1
0.2%
-176.619 1
0.2%
-176.34 1
0.2%
ValueCountFrequency (%)
-179.968 1
0.6%
-179.511 1
0.6%
-179.373 1
0.6%
-178.959 1
0.6%
-178.927 1
0.6%
-178.804 1
0.6%
-178.57 1
0.6%
-178.244 1
0.6%
-178.204 1
0.6%
-178.1 1
0.6%

label
Categorical

 Profiling Report - Train SetProfiling Report - Test Set
Distinct22
Distinct (%)0.4%1.1%
Missing00
Missing (%)0.0%0.0%
Memory size8.4 KiB2.8 KiB
0
327 
1
208 
0
109 
1
70 

Length

 Profiling Report - Train SetProfiling Report - Test Set
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 Profiling Report - Train SetProfiling Report - Test Set
Total characters535179
Distinct characters22
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report - Train SetProfiling Report - Test Set
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling Report - Train SetProfiling Report - Test Set
1st row10
2nd row00
3rd row01
4th row00
5th row10

Common Values

ValueCountFrequency (%)
0 327
61.1%
1 208
38.9%
ValueCountFrequency (%)
0 109
60.9%
1 70
39.1%

Length

2024-11-11T23:14:51.139175image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report - Train Set

2024-11-11T23:14:51.408513image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:51.661349image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 327
61.1%
1 208
38.9%
ValueCountFrequency (%)
0 109
60.9%
1 70
39.1%

Most occurring characters

ValueCountFrequency (%)
0 327
61.1%
1 208
38.9%
ValueCountFrequency (%)
0 109
60.9%
1 70
39.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 535
100.0%
ValueCountFrequency (%)
(unknown) 179
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 327
61.1%
1 208
38.9%
ValueCountFrequency (%)
0 109
60.9%
1 70
39.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 535
100.0%
ValueCountFrequency (%)
(unknown) 179
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 327
61.1%
1 208
38.9%
ValueCountFrequency (%)
0 109
60.9%
1 70
39.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 535
100.0%
ValueCountFrequency (%)
(unknown) 179
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 327
61.1%
1 208
38.9%
ValueCountFrequency (%)
0 109
60.9%
1 70
39.1%

Interactions

Profiling Report - Train Set

2024-11-11T23:14:13.139488image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:36.328604image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:52.278659image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:16.840748image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:56.015385image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:19.019325image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:58.137521image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:21.113997image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:00.534580image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:23.137901image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:02.486540image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:24.989577image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:04.491430image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:27.398941image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:06.715899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:29.594990image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:08.802574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:31.674676image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:11.139683image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:33.809582image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:13.322658image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:36.555096image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:53.671030image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:17.110043image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:56.193770image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:19.212545image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:58.333380image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:21.312522image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:00.739862image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:23.352571image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:02.675768image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:25.220800image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:04.703253image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:27.551779image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:06.963753image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:29.994350image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:09.055423image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:31.863793image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:11.324716image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:34.011789image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:13.476627image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:36.759056image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:53.941604image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:17.417860image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:56.364268image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:19.371184image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:58.502395image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:21.499845image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:00.903302image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:23.509710image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:02.864682image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:25.433959image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:04.903694image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:27.771067image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:07.136752image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:30.170464image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:09.210940image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:32.087734image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:11.487293image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:34.208898image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:13.690278image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:36.976660image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:54.197421image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:17.665485image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:56.570730image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:19.558937image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:58.712340image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:21.721452image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:01.096321image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:23.700927image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:03.073586image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:25.659698image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:05.165068image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:28.024888image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:07.384950image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:30.338165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:09.476945image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:32.341498image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:11.691229image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:34.535831image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:13.863276image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:37.146944image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:54.445232image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:17.813764image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:56.740095image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:19.709076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:58.884982image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:21.885822image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:01.234011image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:23.879178image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:03.259007image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:25.872829image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:05.347574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:28.372841image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:07.545259image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:30.522942image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:09.641346image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:32.540999image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:11.911486image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:34.774342image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:14.062889image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:37.352858image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:54.660260image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:18.016769image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:56.983728image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:20.101229image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:59.085744image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:22.107100image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:01.473881image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:24.047901image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:03.418013image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:26.073164image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:05.555025image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:28.593952image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:07.711791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:30.709526image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:09.819526image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:32.738955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:12.071389image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:35.061481image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:14.307863image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:37.621933image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:54.926789image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:18.199724image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:57.232652image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:20.272853image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:59.290685image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:22.291230image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:01.663483image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:24.236726image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:03.654724image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:26.423629image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:05.791065image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:28.801151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:07.923581image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:30.929096image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:10.097846image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:32.982798image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:12.328824image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:35.475105image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:14.513679image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:37.893624image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:55.206602image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:18.383389image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:57.463792image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:20.498825image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:59.518504image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:22.518925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:01.857004image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:24.392568image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:03.862867image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:26.681108image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:05.962370image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:29.008974image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:08.163855image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:31.096321image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:10.488556image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:33.179110image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:12.498309image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:35.736269image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:14.701361image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:38.145096image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:55.491192image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:18.602749image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:57.695019image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:20.764218image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:59.996867image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:22.722992image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:02.074759image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:24.599553image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:04.068033image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:26.963080image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:06.178215image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:29.186205image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:08.362636image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:31.287565image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:10.742891image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:33.384574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:12.752463image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:35.949069image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:14.926031image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:38.398145image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:55.791092image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:18.818530image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:13:57.968797image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:20.947869image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:00.215281image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:22.965032image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:02.276048image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:24.764553image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:04.230980image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:27.212098image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:06.451746image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:29.390901image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:08.589165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:31.493578image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:10.920904image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:33.560332image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

2024-11-11T23:14:12.943039image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:36.161785image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

Profiling Report - Train Set

2024-11-11T23:14:52.020194image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Test Set

2024-11-11T23:14:52.492000image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Profiling Report - Train Set

cdidepthdmingaplabellatitudelongitudemagTypemagnitudemminetnstsig
cdi1.000-0.0870.1790.1370.2560.166-0.2070.1380.1360.3350.000-0.1930.517
depth-0.0871.0000.030-0.1540.000-0.0680.0530.0000.129-0.2870.0000.0420.036
dmin0.1790.0301.0000.0700.458-0.201-0.0580.136-0.111-0.3100.000-0.820-0.091
gap0.137-0.1540.0701.0000.0620.021-0.3080.318-0.128-0.0150.448-0.0730.005
label0.2560.0000.4580.0621.0000.3190.4050.6010.0000.2130.0520.6300.000
latitude0.166-0.068-0.2010.0210.3191.000-0.1920.173-0.0320.2100.2010.1680.181
longitude-0.2070.053-0.058-0.3080.405-0.1921.0000.1790.039-0.0950.2120.090-0.170
magType0.1380.0000.1360.3180.6010.1730.1791.0000.0000.1050.6660.2750.171
magnitude0.1360.129-0.111-0.1280.000-0.0320.0390.0001.0000.2020.0000.1480.759
mmi0.335-0.287-0.310-0.0150.2130.210-0.0950.1050.2021.0000.1280.1900.382
net0.0000.0000.0000.4480.0520.2010.2120.6660.0000.1281.0000.0000.209
nst-0.1930.042-0.820-0.0730.6300.1680.0900.2750.1480.1900.0001.0000.075
sig0.5170.036-0.0910.0050.0000.181-0.1700.1710.7590.3820.2090.0751.000

Profiling Report - Test Set

cdidepthdmingaplabellatitudelongitudemagTypemagnitudemminetnstsig
cdi1.0000.0450.2110.2090.2600.111-0.1930.1990.2760.3860.000-0.2500.675
depth0.0451.0000.137-0.3100.000-0.110-0.0440.0000.153-0.2320.000-0.0840.060
dmin0.2110.1371.0000.0580.393-0.196-0.1670.1430.025-0.1290.000-0.8150.059
gap0.209-0.3100.0581.0000.135-0.041-0.2570.395-0.0980.1080.4790.0250.049
label0.2600.0000.3930.1351.0000.2870.4120.6340.1830.0000.0000.6170.000
latitude0.111-0.110-0.196-0.0410.2871.0000.0880.022-0.0150.0830.2260.1800.159
longitude-0.193-0.044-0.167-0.2570.4120.0881.0000.3480.0820.0100.3910.174-0.164
magType0.1990.0000.1430.3950.6340.0220.3481.0000.0000.0800.4370.4010.196
magnitude0.2760.1530.025-0.0980.183-0.0150.0820.0001.0000.1450.000-0.0010.670
mmi0.386-0.232-0.1290.1080.0000.0830.0100.0800.1451.0000.1630.0710.408
net0.0000.0000.0000.4790.0000.2260.3910.4370.0000.1631.0000.0000.389
nst-0.250-0.084-0.8150.0250.6170.1800.1740.401-0.0010.0710.0001.000-0.069
sig0.6750.0600.0590.0490.0000.159-0.1640.1960.6700.4080.389-0.0691.000

Missing values

Profiling Report - Train Set

2024-11-11T23:14:15.226936image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.

Profiling Report - Test Set

2024-11-11T23:14:38.699955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.

Profiling Report - Train Set

2024-11-11T23:14:15.701726image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Profiling Report - Test Set

2024-11-11T23:14:39.183684image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Profiling Report - Train Set

magnitudedate_timecdimmisignetnstdmingapmagTypedepthlatitudelongitudelabel
2566.9003-04-2016 08:2376734us01.1725.00mww26.00-14.32166.851
7076.7008-10-2003 09:0606691us5560.0055.40mwc32.0042.65144.570
2946.5023-06-2015 12:1834652us02.2811.00mww460.0027.74139.720
6976.7028-01-2004 22:1506691us2430.0042.50mwb17.40-3.12127.400
826.7027-12-2020 21:3955776us01.3219.00mww10.00-39.33-74.911
6156.6007-11-2006 17:3806670us3520.0018.60mwc11.00-6.48151.190
4307.3027-08-2012 04:3755994us4170.0037.00mww28.0012.14-88.590
5616.9013-06-2008 23:4378888us6540.0017.10mwc7.8039.03140.880
5307.4007-10-2009 23:1307842us3140.0020.20mwc31.10-13.09166.500
4846.7020-12-2010 18:4137708us2790.0024.30mwc12.0028.4159.180

Profiling Report - Test Set

magnitudedate_timecdimmisignetnstdmingapmagTypedepthlatitudelongitudelabel
4736.5011-03-2011 08:1904650us3690.0018.70mb6.8036.17141.560
7427.1026-04-2002 16:0607776us2570.000.00mwc85.7013.09144.620
1366.7001-02-2019 16:1466909us00.2943.00mww66.0014.68-92.451
5266.6008-11-2009 19:4176677us3050.0020.40mwc18.00-8.21118.630
1667.1024-08-2018 09:0403776us03.7712.00mww630.00-11.04-70.830
736.5004-03-2021 23:1204650us011.7625.00mwb24.00-28.48-176.620
5897.0013-09-2007 03:3547768us5370.0023.10mwc22.00-2.1399.630
2626.5011-01-2016 16:3836651us03.1422.00mww13.003.90126.861
4647.6006-07-2011 19:0337893us5670.0033.50mww17.00-29.54-176.340
6396.8005-12-2005 12:1957744us5610.0020.00mwc22.00-6.2229.830

Profiling Report - Train Set

magnitudedate_timecdimmisignetnstdmingapmagTypedepthlatitudelongitudelabel
1236.6014-07-2019 05:3955791us02.9832.00mww10.00-18.22120.360
807.0021-01-2021 12:2375802us02.8215.00mww80.005.01127.521
2556.7006-04-2016 06:5876691us06.7019.00mww24.00-14.07166.621
1726.5015-08-2018 21:5666655us00.5822.00mww33.9351.42-178.031
376.8011-01-2022 11:3576730us00.9261.00mww20.0052.66-167.921
3586.8010-03-2014 05:18551211nc1120.66229.00mw16.4440.83-125.131
2606.6021-01-2016 18:0634673us02.4174.00mww10.0018.82-106.931
6946.7008-02-2004 08:5807691us2560.0033.30mwc25.70-3.67135.340
7716.8028-02-2001 18:54771441uw670.0031.00md51.8047.15-122.730
3246.6007-11-2014 03:3326671us03.5613.00mww53.19-5.99148.231

Profiling Report - Test Set

magnitudedate_timecdimmisignetnstdmingapmagTypedepthlatitudelongitudelabel
3876.6007-07-2013 20:3046674us1390.0014.00mww56.00-6.03149.710
1736.9005-08-2018 11:46981704us02.2715.00mww34.00-8.26116.440
3756.5030-09-2013 05:5504650us01.7121.00mww41.54-30.93-178.321
4396.5011-04-2012 22:55761171us5990.0054.10mwb20.0018.23-102.690
4627.2020-08-2011 16:5586813us2800.0018.40mww32.00-18.36168.140
7136.6021-09-2003 18:1607670us5180.0024.70mwb10.0019.9295.670
6796.6023-10-2004 08:5608670us7820.0037.00mwc16.0037.23138.780
5686.6025-02-2008 18:0646674us4210.0017.70mwc25.00-2.3399.890
5906.5013-09-2007 02:3005650us4090.0026.20mwc28.90-1.6999.670
5077.2004-04-2010 22:40992910ci100.51239.00mw9.9932.29-115.300

Duplicate rows

Profiling Report - Train Set

magnitudedate_timecdimmisignetnstdmingapmagTypedepthlatitudelongitudelabel# duplicates
Dataset does not contain duplicate rows.

Profiling Report - Test Set

magnitudedate_timecdimmisignetnstdmingapmagTypedepthlatitudelongitudelabel# duplicates
Dataset does not contain duplicate rows.